Quantum Channels and Completely Positive Trace-Preserving Maps
Closed quantum systems evolve by a unitary, — reversible, entropy-preserving, information-conserving. No real system is that lucky. Couple a qubit to a warm cavity, send a photon down a lossy fibre, read out a detector, or simply trace away a degree of freedom you no longer control, and the reduced state changes in ways no unitary can produce: pure states go mixed, coherences decay, distinguishability leaks into the surroundings. The object that captures every such deterministic, physically admissible change of a quantum state — and nothing unphysical — is the quantum channel, a completely positive trace-preserving (CPTP) linear map. Three demands fix the definition. Linearity is forced by the statistical reading of : a channel acts on a mixture component by component. Trace preservation, , keeps total probability at one. The third demand is the deep one: it is not enough that send states to states (mere positivity); we require stay positive for any silent reference , because the qubit in your hand may be half of an entangled pair whose partner sits in a distant lab. The transpose passes the single-system test yet fails this one — exactly why it is unphysical. What makes channels beautiful rather than merely careful is that these abstract conditions collapse into concrete, computable representations, each a different window on the same map. Stinespring's dilation builds any channel as a unitary on a larger space followed by a partial trace — "system and environment evolve together, then you forget the environment." The Kraus operator-sum form hands you a short list of matrices to compute with. And the Choi–Jamiołkowski isomorphism folds the whole channel into one bipartite operator whose positive-semidefiniteness is complete positivity. This article proves those equivalences, works them in numbers, and shows why every theorem of quantum Shannon theory — data processing, capacities, the Holevo bound — is a statement about what channels can and cannot do.
- A quantum channel is a linear map that is completely positive and trace-preserving, so it carries states to states even when applied to one half of an entangled pair.
- Complete positivity is strictly stronger than positivity: must stay positive for every . The transpose map is positive but not CP, and that is exactly why no device can implement it.
- Three equivalent pictures hold for any CPTP map — the Kraus form with , the Stinespring dilation , and a positive Choi operator .
- The Choi–Jamiołkowski isomorphism turns " is CP" into the concrete "" — a matrix you diagonalize numerically that encodes the whole channel.
- The data-processing inequality says no channel can raise relative entropy, , so processing never manufactures distinguishability.
- Composition of channels is again a channel, so CPTP maps form a convex monoid; unitary evolution and measure-and-forget are the extreme cases.
- Key idea: a quantum channel is a CPTP map, and complete positivity — positivity preserved even on half of an entangled state — plus trace preservation is exactly the condition for a Kraus/Stinespring representation and a positive-semidefinite Choi matrix to exist.
A quantum channel is a CPTP map; complete positivity (positivity preserved even on half of an entangled state) together with trace preservation is exactly the condition for an operator-sum/Stinespring representation and a positive-semidefinite Choi matrix to exist.
Where this lives today
Quantum channels are the daily language of experimental quantum computing. When a group reports a two-qubit gate fidelity, they have run quantum process tomography or gate-set tomography: prepare a spanning set of inputs, measure the outputs, and fit a Choi matrix subject to and — a semidefinite program that is Choi's theorem in action. The Choi matrix, or its diamond-norm distance to the ideal gate, is the number gates on superconducting, trapped-ion, and photonic platforms are benchmarked against; randomized benchmarking is the scalable shortcut. In error correction, the depolarizing and amplitude/phase-damping channels of this article are the standard noise models whose thresholds decide whether fault tolerance is possible at all. In communication, the complementary channel and the coherent information set the quantum capacity, whose non-additivity remains open research. And the transpose's failure of complete positivity is no curiosity — positivity of the partial transpose is the Peres–Horodecki criterion, one of the most-used entanglement tests in the lab. Wherever a real device meets a decohering world, a CPTP map is the bookkeeping.
The physical picture
Every channel is the same story: unitary on a bigger box, then close your eyes to part of it. Adjoin to your system an environment in a fixed pure state , evolve the pair under a single unitary , then throw the environment away by a partial trace. Whatever irreversible, decohering thing happens to is just the shadow of a reversible evolution on a space you cannot fully see. Stinespring's theorem promotes this from example to law: every channel arises this way, so "open-system dynamics" and "unitary-plus-forgetting" are the same set of maps.
Why demand complete positivity instead of the seemingly sufficient "sends states to states"? Because your qubit may not be alone. Suppose is one half of a Bell pair whose partner sits in a colleague's lab across the country. Whatever the shared correlations, a physical operation on must leave the joint description a legitimate state — no negative probabilities. Positivity of alone does not guarantee this; positivity of does. The transpose is the cautionary tale: it maps every single-qubit state to a valid state, yet applied to half of a Bell pair it yields an operator with a negative eigenvalue — a phantom "state" assigning negative probability to an outcome. Complete positivity is the demand that the map stay sane before any silent spectator. The Choi matrix turns all of this into linear algebra. Feed half of an unnormalized maximally entangled vector through the channel and out comes one bipartite operator that fingerprints the whole map: its positivity is complete positivity, its output partial trace equalling the identity is trace preservation, and its rank counts the minimal Kraus operators. Abstract questions about superoperators become concrete questions about the eigenvalues of one matrix — and the next figure runs exactly that test on a real channel and on the transpose counterexample.
Finally, channels compose: is again CPTP. This monoid structure, with the identity channel as unit, is why information can only degrade along a processing chain — every extra channel is another chance to lose distinguishability, never to regain it. That is the data-processing inequality, and why "post-processing cannot help" is a theorem rather than a slogan.
The core equations
A channel is fixed by two conditions: it preserves the probabilistic normalization and keeps every extended state legitimate. The first line states the state-to-state consequence; the deeper condition, complete positivity, gets its own equation next.
where: — input density operator on ; — linear superoperator ; — positive semidefinite. Reading: valid states go to valid states, but this single-system condition is necessary and not sufficient. Complete positivity demands the map stay positive even acting on a subsystem of a larger, possibly entangled, whole — and one need only test a reference as large as the input.
where: — do-nothing channel on a spectator ; — any positive operator on . Reading: positivity must survive a silent bystander; the transpose fails here despite passing (1), which is exactly why CP is the right notion. The Kraus or operator-sum form is the computational workhorse: a finite sum of "sandwich" terms whose completeness relation is trace preservation.
where: — Kraus operators , at most of them; — completeness, equivalent to . Reading: summing the branches incoherently is what makes the evolution non-unitary. Stinespring's dilation is the physical origin of the Kraus form — an isometry into a larger space, then discard the added factor. It is the equation behind the first figure.
where: — isometry ; — partial trace over the environment. Reading: (not ) embeds into a corner of the bigger space; forgetting injects the noise. The Choi–Jamiołkowski isomorphism folds the whole channel into one operator on the doubled space by running half of a maximally entangled vector through it.
where: — Choi operator on ; — unnormalized maximally entangled vector of norm . Reading: is a bijection — "channel–state duality" — so channel questions become state questions. The payoff is a concrete validity test: complete positivity becomes a matrix being positive, trace preservation becomes a partial-trace condition.
where: — equivalent to complete positivity; — equivalent to trace preservation. Reading: two checks on one matrix replace the "for all reference systems" quantifier of (2). The inverse isomorphism reconstructs the channel's action from its Choi operator, closing the dictionary.
where: — transpose of the input in the basis; — partial trace over the input-copy register. Reading: channel and Choi matrix carry identical information. Because every channel is an isometry plus a partial trace, and neither raises distinguishability, relative entropy can only fall — the master monotonicity of the theory.
where: — quantum relative entropy; — any CPTP map on both arguments. Reading: no processing makes two states easier to tell apart — the data-processing inequality, parent of the Holevo bound and capacity converses. The dilation defines a second channel for free: keep the environment instead of the output. That complementary channel governs how much information leaks away.
where: — complementary channel ; — trace out the output instead of the environment. Reading: and are two halves of one isometry, and their interplay (degradability) fixes the quantum capacity.
The goal is to build the Kraus form of a channel from the most physical picture available — a system coupling to an environment prepared in a fixed pure state, the pair evolving under one unitary, and the environment then discarded — and to prove this "unitary-plus-forgetting" construction always yields a completely positive, trace-preserving map. We read off the operators and show their completeness relation is nothing but unitarity in disguise.
Step 1. Evolve the joint system with the environment in a fixed pure state: , unitary on . Why: this is the only assumption — a closed enlarged system evolving reversibly.
Step 2. Discard the environment by a partial trace in a basis : . Why: forgetting the environment is the origin of irreversibility — an incoherent sum over its "which-way" records.
Step 3. Define , an operator on . Substituting gives the operator-sum form . Why: the environment indices are packaged into a finite list of system operators with no information lost.
Step 4. Check completeness from unitarity: , so . Why: trace preservation is not an extra assumption — it is unitarity, expressed on the reduced system.
Step 5. Bound the count: Choi's theorem (next) shows the Choi matrix has rank at most , so a channel never needs more than Kraus operators — at most four for a qubit — and any two Kraus sets differ by an isometry on the operator index. Why: this makes the operator-sum form a finite, canonical object. *Verified: reproduces Nielsen & Chuang Theorem 8.1; checked numerically for amplitude damping.*
Go deeper · Derivation B · 1 minComplete positivity equals a positive Choi matrix
The goal is to prove Choi's theorem: the abstract requirement that preserve positivity in every dimension is equivalent to the single checkable statement that the Choi operator is positive semidefinite. The forward direction is immediate; the reverse is substantive and simultaneously delivers the Kraus decomposition, tying representations (3), (5), and (6) together. We show CP implies , then implies a Kraus form, then a Kraus form is manifestly CP.
Step 1. Forward: is a legitimate positive operator, so if preserves positivity then at once. Why: complete positivity applied to one input already forces .
Step 2. Reverse, spectral step: assume and diagonalize it as with , absorbing eigenvalues into the eigenvectors. Why: positivity is exactly what lets split into rank-one positive pieces; the number of terms is the Kraus rank.
Step 3. Vectorize each eigenvector into an operator via — the Choi–Jamiołkowski correspondence between bipartite vectors and operators . Why: undoing the doubled-space bookkeeping turns each into an honest channel operator.
Step 4. Reconstruct with (7): , a sum of sandwiches and hence manifestly CP. Why: any operator-sum map is automatically CP even under tensoring with a reference, so has produced a certificate of complete positivity.
Step 5. Trace condition: , equal to precisely when is trace-preserving. Why: the two clauses of (6) separate cleanly — is CP, is TP. *Verified: reproduces Choi (1975) and Watrous Thm 2.22; the contrapositive checked on the transpose map, whose Choi = SWAP has eigenvalues {+1, +1, +1, −1}.*
Go deeper · Derivation C · 1 minThe data-processing inequality from Stinespring dilation
The goal is to prove that no quantum channel can increase the relative entropy between two states — — by reducing an arbitrary channel to its two dilation ingredients and handling each separately. Only two facts are needed: relative entropy is exactly invariant under an isometry (which merely relabels states into a larger space), and it is non-increasing under a partial trace (the deep input, equivalent to strong subadditivity). Chaining them along the dilation gives the theorem for every CPTP map at once.
Step 1. Dilate: by Stinespring, for an isometry . Why: this splits the channel into a reversible embedding and a single irreversible act — discarding — treated independently.
Step 2. Isometric invariance: . Why: an isometry preserves eigenvalues and overlaps, hence every spectral functional; the embedding is "free" and cannot change distinguishability.
Step 3. Partial-trace monotonicity: . Why: this single inequality is the entire content of data processing and is equivalent to strong subadditivity — the hardest entropy inequality in the subject.
Step 4. Combine: for arbitrary CPTP . Why: the steps compose along the dilation, so "you cannot beat data processing" is structural, not case-by-case. *Verified: equivalent to Lindblad–Uhlmann monotonicity, consistent with Wilde Ch. 11.*
Limiting cases
The CPTP definition contains every familiar kind of evolution as a special case — from perfectly reversible to maximally destructive, down to ordinary classical noise.
| Case | Result | Meaning |
|---|---|---|
| Unitary (closed) evolution | A single Kraus operator with ; reversible, entropy- and eigenvalue-preserving. The invertible extreme points of the channel set. | |
| Completely depolarizing | Sends every input to the maximally mixed state — total erasure. Its Choi operator is the product , the noisiest channel of all. | |
| Measure-and-forget (pinching) | A projective measurement whose outcome is discarded; with it kills off-diagonal coherence in the basis — pure dephasing. | |
| Isometric channel | A single Kraus operator embedding into a larger space — the Stinespring isometry itself. Entropy-preserving, reversible by on its image. | |
| Classical stochastic map | Restricted to diagonal states, a channel collapses to a column-stochastic matrix — a classical Markov channel. Quantum channels strictly contain these. |
Worked examples
1 · The amplitude-damping channel is CPTP — proved by its Choi matrix (fully worked)
The amplitude-damping channel models energy relaxation ( decay): an excited qubit emits a photon into the environment with probability . Its Kraus operators are and . Show it is a valid channel, and verify complete positivity numerically at .
Step 1. Check the completeness relation (trace preservation). Compute and . Their sum is . So and the channel is trace-preserving. The Kraus set is complete.
Step 2. Build the Choi matrix . The Kraus operators give , , . In the basis (first index output ) the nonzero entries are , , , .
Step 3. Diagonalize. The subspace decouples into the block with diagonal entries and and off-diagonal entry ; it has trace and determinant , so its eigenvalues are and . The remaining diagonal entries contribute and . Hence the four Choi eigenvalues are , all for . The channel is completely positive.
Step 4. Insert : the eigenvalues are — exactly the green bars in the second figure. The Choi rank is , matching the two Kraus operators, and confirms trace preservation again. At the Choi spectrum is , so amplitude damping is CPTP.
2 · The transpose map fails — the canonical counterexample (fully worked)
Show that the transpose , though positive and trace-preserving on a single qubit, is not a quantum channel, by computing what it does to half of a Bell state and by inspecting its Choi operator.
Step 1. Take the Bell state , with density matrix having entries at positions ; ; ; . Apply to the second qubit only (the partial transpose), which swaps the and index pairs. The result is the partial transpose .
Step 2. Diagonalize the partially transposed matrix. Its eigenvalues are — three positive and one negative. A genuine density operator cannot have a negative eigenvalue, so has produced a non-state. The eigenvalue is the smoking gun: is not completely positive.
Step 3. Confirm via the Choi operator. By definition , precisely the SWAP operator — eigenvalue on the symmetric subspace and on the antisymmetric one, spectrum (the blue-and-red bars in the second figure). Since , the Choi criterion (6) rejects . is positive and trace-preserving yet not CP, so it is no channel — but the partial transpose it defines is exactly the Peres–Horodecki entanglement test.
3 · How much a depolarizing channel shrinks the Bloch sphere
The single-qubit depolarizing channel is . Writing , find how the Bloch vector transforms, and evaluate at .
Step 1. Each Pauli conjugation flips the sign of the two components orthogonal to its axis, so . The three-term sum triples but reverses .
Step 2. Assemble: , so . The channel shrinks every Bloch vector isotropically by .
Step 3. At the factor is , so a length- vector maps to . At it is — the channel becomes completely depolarizing and erases all information, the third row of the limiting-cases table. At the sphere shrinks to 60% of its radius; collapses it to the centre.
Physics of the portrait
The theory of quantum channels was assembled between the mid-1950s and mid-1970s by mathematicians studying positive maps on operator algebras, before physicists had a name for the objects. Its keystone — that the elusive "complete positivity" is nothing more than a positive matrix — belongs to one person.
Origins · 1 minMan-Duen Choi and how this was discovered
Man-Duen Choi is a Hong Kong-born mathematician who spent his career at the University of Toronto in operator theory and matrix analysis. In a single 1975 paper — Completely Positive Linear Maps on Complex Matrices — he proved the result now bearing his name: a linear map on matrices is completely positive if and only if its Choi matrix is positive semidefinite, equivalently if and only if it admits an operator-sum form . At the time this was pure finite-dimensional operator algebra descending from Stinespring's 1955 dilation theorem; the word "qubit" would not exist for two decades. Yet Choi had handed quantum information its most-used computational tool — the reason channel validity is a semidefinite feasibility problem, process tomography a convex optimization, and "is this map physical?" a single Hermitian-matrix diagonalization. The channel–state isomorphism his construction encodes had been noted independently by Andrzej Jamiołkowski in 1972 (hence Choi–Jamiołkowski), the operator-sum picture written by Karl Kraus in 1971, and the structural core is Stinespring's. But it was Choi's positivity criterion that made the edifice calculable, turning "positive on every extension" into a finite eigenvalue check a laptop runs in microseconds.
Going further
Texts. Nielsen & Chuang, Quantum Computation and Quantum Information, Ch. 8 (quantum noise and quantum operations) · Preskill, Lecture Notes for Physics 219, Ch. 3 (measurement and evolution) · Watrous, The Theory of Quantum Information, Ch. 2 (linear maps and channels) · Wilde, Quantum Information Theory, Ch. 4 (the noisy quantum channel) and Ch. 11 (quantum entropy and data processing) · Kitaev, Shen & Vyalyi, Classical and Quantum Computation, section on superoperators · Choi, Completely Positive Linear Maps on Complex Matrices, Lin. Alg. Appl. 10 (1975) 285.
Provenance. The CPTP definition and the three representations follow Nielsen & Chuang Ch. 8, Preskill Ch. 3, and Watrous Ch. 2. A verifier should recompute: (1) the transpose counterexample — partially transposed Bell state eigenvalues and eigenvalues ; (2) the amplitude-damping Choi spectrum , giving at with ; (3) the depolarizing Bloch shrink , equal to at and at . The data-processing proof reduces to Lindblad–Uhlmann monotonicity (Wilde Ch. 11). All quoted numbers were independently reproduced numerically for this article.
Builds on: Density operators and the trace · Tensor products and partial trace · Von Neumann Entropy · Quantum Relative Entropy. Leads to: Kraus Representation of Quantum Channels · Stinespring Dilation Theorem · Choi–Jamiołkowski Isomorphism · Complementary Channels and Degradability · Data-Processing Inequality · Holevo Bound.
Ask the tutor: Want to see the amplitude-damping Choi matrix diagonalized entry by entry, or watch the data-processing inequality collapse three states through a noisy channel — just ask.
What is the difference between positivity and complete positivity?
Positivity means the map sends every density matrix to a valid (positive) operator; complete positivity means it does so even when acting on just one part of a larger system entangled with a spectator. The gap is not academic — the matrix transpose is positive but not completely positive, and that single distinction separates physically implementable maps from merely mathematically positive ones. Formally is completely positive if is positive for every , and Choi's theorem shows testing suffices.
Why do we need three different representations of the same channel?
Because each answers a different question with almost no effort. The Kraus form is best for computing an output or simulating noise — you just sum . The Stinespring dilation is best for proofs and intuition, since it exhibits the environment and makes data processing a two-line argument. The Choi matrix is best for deciding validity and for experiment: complete positivity becomes an eigenvalue check and tomography becomes a semidefinite program. Choi's theorem is the bridge that lets you convert freely and reach for whichever makes the task trivial.
How many Kraus operators does a channel actually need?
At most , the product of input and output dimensions, which equals the rank of the Choi matrix. For a qubit channel that ceiling is four: a unitary needs one, dephasing two, amplitude damping two, and the fully depolarizing channel the full four. The minimal number is exactly the Choi rank, and any two minimal Kraus sets are related by a unitary mixing the operator index — so "the" Kraus operators are defined only up to that freedom, much as a mixed state's pure-state ensemble is not unique.
Is a measurement a quantum channel?
Yes, if you discard the outcome. A generalized measurement with operators gives outcome with probability and post-state renormalized. Keep the classical outcome and you have a quantum instrument; throw it away and average, and you get the deterministic channel with — an ordinary CPTP map. This is why "measure and forget" is a limiting case: measurement, decoherence, and dissipation are all channels, differing only in whether their environment records are read.
Why can't a channel ever increase distinguishability?
Because a channel is the composition of two harmless steps — embed the state into a larger space by an isometry, then discard part of it — and neither helps you tell states apart. The isometry preserves relative entropy exactly (it just relabels), and the partial trace can only decrease it. Their composition therefore never increases , the data-processing inequality. Every converse bound in quantum Shannon theory — capacity upper bounds, the Holevo bound, the impossibility of amplification by cloning — is ultimately this one fact in different clothes.
What is the complementary channel and why should I care?
It is what the same Stinespring dilation gives when you keep the environment and discard the output: . It captures the information that leaked away rather than what came through. This matters because quantum capacity is governed by the coherent information , a competition between what the output keeps and what the environment steals — a quantum echo of no-cloning. When is a post-processing of (a degradable channel) the coherent information is additive and the capacity simplifies; otherwise capacities can be superadditive and the theory turns hard.
Is the Choi matrix the same thing as a density matrix?
Almost — it is one up to normalization. For a trace-preserving channel with , so dividing by gives a genuine bipartite state, the Jamiołkowski state of the channel. This is the precise sense of channel–state duality: every channel corresponds to a state on the doubled space, and channel properties (capacity, entanglement-breaking, noisiness) become properties of that state. The correspondence is a bijection, so nothing is lost — which is why process tomography can borrow the whole toolkit of state tomography.